Research framework for low resource text classification that allows the user to experiment with classification models and active learning strategies on a large number of sentence classification datasets, and to simulate real-world scenarios. The framework is easily expandable to new classification models, active learning strategies and datasets.
I was getting an OOM error with larger datasets even with a smaller batch size and model (base with batch 10):
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[10,100,3072] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:Erf]
The lines that were causing it are those changed in the commit. I found that keeping a list of the model calls was using uneccessary memory during evaluation and it works after this change.
(Also I would like to add that I really appreciate how organised and well documented this repository is!)
I was getting an OOM error with larger datasets even with a smaller batch size and model (base with batch 10):
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[10,100,3072] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:Erf]The lines that were causing it are those changed in the commit. I found that keeping a list of the model calls was using uneccessary memory during evaluation and it works after this change. (Also I would like to add that I really appreciate how organised and well documented this repository is!)